OptaPro speaks with Antonio Tramontano, match analyst at Chinese Super League side Tianjin Quanjian. Sitting fourth in the CSL at the time of the interview, the team is coached by 2006 World Cup and Ballon d'Or winner Fabio Cannavaro, who joined the club in June 2016.

Antonio graduated from the University of Naples with a sports science degree before completing his UEFA B licence. Ahead of his move to Tianjin Quanjian, Antonio worked as part of the FIGC (Italian Football Federation) match analysis department.

This interview was originally conducted in Italian and has been translated into English.

Antonio, thank you for taking the time to speak with us. To begin, could you please talk though how you use and apply data on a weekly basis, particularly in regards to pre-match analysis?

I consider data analysis a fundamental part of my work in preparation for a match. Before watching games of our upcoming opponent, I will start to analyse the data to have an idea of their strengths and weaknesses.

For instance, when studying their average positions or their defensive line I can make an initial note on their on-field behaviour and tendencies. I always aim to create a report where data, video and personal opinions are integrated, giving layers of objectivity and subjectivity to my work.

Data can lead my focus on specific topics that I’ll follow-up with video analysis, however video analysis can also be the lead and help inform data analysis.

My opposition reports are broken down into different parts: the first focuses on recent opposition games, then there is a focus on the team’s attacking and defensive patterns – both in open play and at set pieces. Each of these sections has sub-categories: for example, in the attacking analysis I underline the style of play of the team in possession, providing images and videos along with data and graphics.

The reports are always flexible in terms of topics and structure, and my first task is to respond to the coach’s needs. I have to know his ideas and schemes of football perfectly. Every game brings different problems and requirements to light so we need to adapt and be flexible, catching those little details that can support and improve the team.

And what about post-match analysis?

After the game, I start to analyse the Opta data, keeping in mind my coach’s ideas, and trying to pull out items he can use to evaluate team performance.

The second step in the process concerns video, however it will be the decision of the coaches if this gets shown to the team or not.

In the post-match evaluation, we also need to analyse positive or negative trends across the short, medium and long term, consistently monitoring those details the coach focuses on during the season.

As I’ve said before, we have to be flexible because while it is important to have a weekly plan and consistent processes, there are also areas of reactivity and we must be prepared for that. With a match taking place every three or four days, this often influences the work we can do.

Could you please tell us a bit about how you work with the coaches and players?

After reviewing and filtering the data and video, the coach then chooses what to present and share with the team. All the information provided must be concise and immediately accessible, so data is often presented to the players with the support of graphics and tables, with video following.

These tools provide so much help in breaking down the language and cultural barriers that can exist in a league like the Chinese Super League, helping us to deliver straightforward messages with maximum clarity.

Different managers can have different views of data and its potential impact. How does Fabio Cannavaro view performance data?

Our coach is a diligent manager, he doesn’t leave anything to chance on the pitch and outside of the pitch.

To better understand the coaching staff’s attitudes toward data you need to imagine a puzzle. The puzzle is the preparation for the next game which is made up of many different pieces. Individual pieces don’t really mean anything, but if you put together training sessions, group management, video and data analysis, and all other factors that prepare the team for the game, then the puzzle becomes clear and has a meaning.

For Mr. Cannavaro and me, data is an important part of a bigger picture of work, in both the short and long term.

Thank you Antonio. We have one final question: in your opinion, how has the use data has changed over the past five years and how has it impacted match analysis?

I’m 28 years old, which means I’m young and I started working in football while big data took on more importance. This is increased importance is also due to the better technologies we have now to study and analyse what happens during a game.

But we do not think we are better than our older match-analyst colleagues, nowadays we are just using the very best technologies and have a wider pool of knowledge that we can apply to football.

What I like of my role is that I see football as something to study and something that is always changing and evolving. Data helps me to better understand the game.

But I want to be clear that there isn’t any conflict between old and new generations, today we just try to improve in understanding this sport, and the match-analyst is a trainer appointed to work with data and video in order to support the head coach.